Networked image/video processing system and network site therefor

ABSTRACT

A distributed image/video processing system is disclosed herein wherein one or more of digital image/video recorders (e.g., a digital cameras, video recorders, or smart phones, etc.) are in network communication with central network site for transmitting image or video data thereto. The recorders process their image/video data dependent upon an estimate of a measurement of network bandwidth that is available for transmitting image or video data to the central network site.

FIELD OF THE INVENTION

The present application is directed to distributed processing of data ona network wherein the processing performed at a client network node isat least partially determined according to network transmissioncharacteristics or constraints, and more particularly, the presentapplication is directed to such distributed processing when the data isimage or video data.

BACKGROUND

Processing pictorial (image) and/or video digital data can be bothcomputationally intensive and consume large amounts of data storage. Formany communication devices (e.g., mobile phones) having capabilities forgenerating digital images (photos) and/or videos, these devices haveprocessing and/or storage capacities that are insufficient toappropriately wholly reside on the devices. Accordingly, it is desirableto store and in some cases at least partially process such image/videodata at one or more central sites on a communications network whereinsuch sites have relatively large data processing and storage capacities.However, the network can be significantly degraded if large numbers ofnetwork users transmit image/video data to such central network sitesdue to the corresponding high data volume image/video data that may betransmitted on the network. Accordingly, one solution would be to limitthe amount of image/video data that users transmit on the network, e.g.,during a day, week or month. This solution has significant drawbacks inthat network users increasingly believe that a “smart”telecommunications network should “intelligently” perform user networkrequests to the degree possible, and further that such requests shouldbe performed without requiring the users to have relatively detailedknowledge of network communications.

Thus, to address the above problem, it is desirable to provide a more“intelligent” technique for managing and transmitting image/video dataon a telecommunications network. In particular, it would be desirable todynamically vary the amount of image/video data that users transmit onthe network according to current network transmission characteristics,wherein such dynamic varying of network transmissions is performedsubstantially transparently to the users, and wherein the presentationor display quality of such image/video data can be substantiallymaintained.

SUMMARY

A distributed image/video processing system is disclosed herein whereinone or more (preferably a plurality) of digital image or video recorders(each being, e.g., a digital camera, video recorder, or multi-purposedevice such as a smart phone, or computer laptop) is in networkcommunication with central network site for transmitting image or videodata thereto. The recorders process their image or video datasubstantially dependent upon an estimate of an amount or measurement ofnetwork bandwidth that is available for transmitting the image or videodata (or a version thereof) to the central network site. Moreparticularly, the recorders perform image or video processing on suchcaptured image/video data as appropriate to maintain an acceptablyefficient (fast) transmission time of the recorder processed image/videodata to the central network site. In particular, each such recorderperforms image/video enhancement processes and image/video compressiontechniques in a manner that varies the amount of resulting image/videodata transmitted on the network according to a measurement of networkbandwidth currently available.

In one embodiment, the phrase “network bandwidth currently available”and similar equivalent phrases such as “available network bandwidth”refers to a difference between an estimated reasonable maximum data rateor through put of the network between two predetermined networkconnection points, and an estimate of an actual current data rate orthrough put of the network between the two predetermined networkconnection points at a particular time or in a particular time interval.Assuming there is at least a general estimate of the data rate orthrough put of the network between two predetermined network connectionpoints wherein this general estimate is considered to be a reasonablemaximum (given that varying network configurations and network trafficbalancing may occur), the “available network bandwidth” may be estimatedby measuring one or more current network data transmission rates or datathroughputs at one or more particular network sites (e.g., one or bothof the two predetermined network connection points), determining acomposite (e.g., average) current network data transmission rate or datathroughput therefrom, and then subtracting the composite current datatransmission rate or data through put from the general (maximum)estimate. Alternatively, such a reasonable maximum estimate of thenetwork bandwidth may be determined by using network transmission timedelays, e.g., between two network connection points. For example, such amaximum bandwidth estimate may be determined from measuring time delaysfor one or more pings between, e.g., the two predetermined networkconnection points as one skilled in the art will understand. Forexample, if a maximum acceptable time delay between the two networkconnection points is determined, then an indication of an availablenetwork bandwidth may be determined by subtracting a current (or mostrecent) measurement of a network time delay(s) between the two networkconnection points from the maximum acceptable time delay to estimate the“available network bandwidth.” Note that whereas a measurement of the“available network bandwidth” based on data transmission rates orthroughput is monotonically increasing with the above describeddifference in data transmission rates or throughput, a correspondingmeasurement of “available network bandwidth” based on network timedelays is inversely related to the above described differences networktransfer time delays.

In one embodiment, measurements of available network bandwidth may bedetermined by analyzing historical measurements of network data ratesand/or (ping) time delays, and making a determination as to whatmeasurement should be designated as a reasonable maximum estimate of thenetwork bandwidth. For example, such a reasonable maximum estimate maybe taken to be, e.g., boundary value between first and second standarddeviations of the historical measurements as one skilled in the art willunderstand.

Accordingly, when available network bandwidth is low (e.g., relative tothe type, size or data rate of data to be transferred), such animage/video recorder will perform image/video enhancement processes in amanner that reduces (or does not appreciably increase) the amount ofdata, and then compresses the enhanced image/video data with anaggressive compression technique that may substantially reduce theamount of resulting image/video data to be transferred on the network tothe central network site, thereby reducing the impact on the availablenetwork bandwidth over what such impact would be if, e.g., little or nocompression where performed. Moreover, in order to maintain the displayquality of the image/video data, noise reduction techniques are alsoapplied to the image/video data by the recorder in a manner dependentupon an amount of data compression to be applied prior to networktransmission to the central site. For example, more robust noisereduction (also referred to herein as “de-noising”) is applied to imagedata when the recorder determines that a more aggressive datacompression technique is to be also applied. Thus, the increasedde-noising will negate at least some of the effects of the increaseddata compression so that data for an acceptable quality of image displaycan be maintained while reducing the volume of network traffic.

In at least one embodiment, the image/video processing system disclosedherein obtains or reads a first network parameter data indicative of apreferred size of image data for transferring on the network. Since thesize of the image initially captured by a recorder is typicallyavailable to the recorder, a compression factor can be computed (i.e.,size of the capture image divided by preferred image size).Additionally/optionally, a second parameter data indicating the datacompression type to perform may be provided via being read from anetwork transmission (e.g., transmitted from a predetermined networksite), or, alternatively, the compression type may be determined by therecorder (e.g., the recorder may determine an available compression typethat provides the desired compression factor and is the least lossy).Given such a compression factor, and compression type (e.g., Loss Less,or JPEG), a table (or other data structure) resident at the recorder canbe accessed to determine corresponding enhancement processes (andparameters therefor) such as de-noising and sharpening processes toperform.

Note that similar determinations can be made for video data. Forexample, if the network provides a preferred transmission data rate,then assuming the recorder has access to the video data rate (e.g.,Kbps) being received by the recorder, a video compression factor candetermined for corresponding transmissions on the network. Additionally,a compression type can be determined either from being read from anetwork (or network site) transmission, or, alternatively, thecompression type may be determined by the recorder, wherein the recordermay determine an available compression type that provides the desiredcompression factor and is the least lossy.

Accordingly, assuming (i) the recorder has access to one or more of thetables (or corresponding data structures) providing the information forcaptured image sizes and/or video data rates), and assuming (ii) therecorder also has access to desired or preferred a image/video networktransmission attributes (e.g., size or data rate), then such tables canbe accessed by the recorder to determine at least the type ofde-noising, sharpening, and compression processes to be applied, as wellas the parameters for operably configuring each of these processes.Thus, even though much of the description herein is illustrative of suchprocesses being dependent upon available network bandwidth, other knownor unknown constraints/conditions (e.g., substantially unrelated toavailable network bandwidth) may be involved in determining the desiredor preferred a image/video network transmission attributes.

In one embodiment, the image/video processing system disclosed hereinperforms the following steps:

(a) receiving at a network site, via one or more network transmissions,processed data and a corresponding history information of processingperformed for obtaining the processed data, wherein the processingperformed depends on network data related to a transmissioncharacteristic of the network, the network data obtained for determiningthe processing;

(b) accessing the history information for determining: decompressioninformation related to the processed data, and enhancement informationrelated to enhancing a visual presentation of the processed data;

(c) decompressing the processed data, thereby obtaining decompresseddata, wherein the decompression information indicates a decompression tobe performed on the processed data; and

(d) enhancing one of: the processed data or the decompressed dataaccording to the enhancement information; and

wherein the step of enhancing includes a step of activating one or moreof: a de-noising process, a sharpening process, an auto-exposureprocess, an auto-white balance process, and an auto-focus process forobtaining the enhanced visual presentation.

In one embodiment, the image/video processing system disclosed hereincan be characterized as a non-transitory computer-readable medium havingmachine instructions stored thereon, the instructions comprising:

(a) receiving at a network site, via one or more network transmissions,processed data and a corresponding history information of processingperformed for obtaining the processed data, wherein the processingperformed depends on network data related to a transmissioncharacteristic of the network, the network data obtained for determiningthe processing;

(b) accessing the history information for determining: decompressioninformation related to the processed data, and enhancement informationrelated to enhancing a visual presentation of the processed data;

(c) decompressing the processed data, thereby obtaining decompresseddata, wherein the decompression information indicates a decompression tobe performed on the processed data; and

(d) enhancing one of: the processed data or the decompressed dataaccording to the enhancement information; and

wherein the step of enhancing includes a step of activating one or moreof: a de-noising process, a sharpening process, an auto-exposureprocess, an auto-white balance process, and an auto-focus process forobtaining the enhanced visual presentation.

In one embodiment, the image/video processing system disclosed hereincan be characterized as a system for processing image or video datacomprising:

a network site including the following (a) through (c):

-   -   (a) a network interface for receiving, via one or more network        transmissions, processed data and a corresponding history        information of processing performed for obtaining the processed        data, wherein the processing performed depends on network data        related to a transmission characteristic of the network, the        network data obtained for determining the processing;    -   (b) a decompressor for decompressing the processed data;    -   (c) a controller for configuring, using the history information,        the decompressor for decompressing the processed data resulting        in decompressed data, and for configuring one or more        enhancement processes for enhancing the decompressed data,        wherein the enhancement processes include at least one noise        reduction process for reducing a noise for the decompressed        data, and at least one sharpening process for sharpening a        presentation for the decompressed data;

wherein the history information identifies processing of image or videodata to yield the processed data, wherein the history informationincludes: (i) compression description information related to which of afirst and second data compressions were performed in obtaining theprocessed data, and (ii) enhancement description information indicativeof image or video enhancement processes performed in obtaining theprocessed data.

Further description of the advantages, benefits and patentable aspectsof the present disclosure will become evident from the descriptionhereinbelow and the accompanying drawings. All novel aspects of thedisclosure, whether mentioned explicitly in this Summary section orotherwise (e.g., hereinbelow), are considered subject matter for patentprotection either singly or in combination with other aspects of thisdisclosure. Accordingly, such novel aspects disclosed hereinbelow and/orin the drawings that may be omitted from, or less than fully describedin, this Summary section are fully incorporated herein by reference intothis Summary. In particular, all claims of the Claims sectionhereinbelow are fully incorporated herein by reference into this Summarysection.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram showing the high level computationalcomponents of an embodiment of the distributed image/video processingsystem 10 disclosed herein.

FIG. 2 is a flowchart illustrating an embodiment of the steps performedby the distributed image/video processing system 10 disclosed herein.

DETAILED DESCRIPTION

Introductory Remarks.

For the purposes of promoting an understanding of the principles setforth in the present disclosure, reference will now be made to exemplaryembodiments. Any alterations and further modifications of the inventivefeatures illustrated herein, and any additional applications of theprinciples illustrated herein, which would occur to one skilled in therelevant art and having possession of this disclosure, are to beconsidered within the scope of the invention as described in the claimsfollowing this Detailed Description section. The features, functions,and the like described herein are considered to be able to be combinedin whole or in part one with another as the claims and/or art maydirect, either directly or indirectly, implicitly or explicitly.

Reference throughout this specification to an “embodiment,” an “example”or similar language means that a particular feature, structure,characteristic, or combinations thereof described herein may, but do notnecessarily, refer to the same embodiment, to different embodiments, orto embodiments disclosed in one or more of the figures.

Many of the functional units described in this specification may belabeled or identified as modules or computational components, in orderto more particularly emphasize their implementation independence. Forexample, a module may be implemented as a combination of hardware andcorresponding software substantially independently from other suchmodules or computational components.

Modules or computational components (e.g., computational machines,equipment, devices, etc.), such as those identified by boxes in FIG. 1described hereinbelow, may comprise one or more physical or logicalblocks of computer instructions which may, for instance, be organized asan object, procedure, or function. Nevertheless, the executable versionsof such modules or computational components need not be physicallylocated together (unless stated or implied otherwise), but may comprisedisparate instructions stored in different locations which, when joinedlogically together, comprise higher level modules or computationalcomponents for achieving a particular stated purpose.

Moreover, a module, computational component and/or a program ofexecutable code may be a single instruction, or many instructions, andmay even be distributed over several different code segments, amongdifferent programs, and across several non-transitory memory devices.Similarly, operational data may be identified and illustrated herein forsuch modules or computational components, and may be embodied in anysuitable form and organized within any suitable type of data structure.Such operational data may be collected as a single data set, or may bedistributed over different locations including over differentnon-transient storage devices, and may exist, temporarily, merely aselectronic signals on a system or network.

The various computational components and/or modules discussed herein mayinclude one or more of a communications network host server or othercomputing systems which may include: (i) a machine processor forprocessing digital data; (ii) a non-transitory memory coupled to theprocessor for storing digital data; an input digitizer coupled to theprocessor for inputting digital data; (iii) an application programstored in the memory and accessible by the processor for directingprocessing of digital data by the processor; (iv) a display devicecoupled to the processor and memory for displaying information derivedfrom digital data processed by the processor; and (v) a plurality ofdatabases including corresponding database management systems. As thoseskilled in the art will appreciate, any computers or computationalmachinery discussed herein may include an operating system (e.g.,Windows 7, Windows Vista, NT, 95/98/2000, OS2; UNIX; Linux; Solaris;MacOS, Snow Leopard; etc.) as well as various conventional supportsoftware and drivers typically associated with computers and/or anetwork of computers. The computers or computational machinery may be ina home, a business environment with access to the network, or suchmachinery may be mobile such as a mobile phone or other transportabletelecommunications device. In an exemplary embodiment, access is throughthe Internet through a commercially-available web-browser softwarepackage.

The present disclosure may be described herein in terms of functionalblock components, screen shots, user interaction, optional selections,various processing steps, and the like. It should be appreciated thatsuch functional blocks may be realized by any number of hardware and/orsoftware components configured to perform the specified functions.Accordingly, embodiments disclosed herein may employ various integratedcircuit components, e.g., memory elements, processing elements, logicelements, look-up tables, and the like, which may carry out a variety offunctions under the control of one or more microprocessors or othercontrol devices. Similarly, the software elements of the presentdisclosure may be implemented with any programming or scripting languagesuch as C, C++, Java, COBOL, assembler, PERL, Visual Basic, SQL StoredProcedures, AJAX, extensible markup language (XML), and/or SOAP, withthe various algorithms being implemented with any combination of datastructures, objects, processes, routines or other programming elements.Further, it should be noted that the present disclosure may employ anynumber of conventional techniques for data transmission, signaling, dataprocessing, network control, and the like. Still further, embodiments ofthe invention claimed herein may detect or prevent breaches in securitywith a client-side or host-side scripting language, such as JavaScript,VBScript or the like.

Additionally, many of the functional units and/or modules herein may bedescribed as being “in communication” or “in operable communication” (orvariations of such phrases) with other functional units and/or modules.Being “in communication” or “in operable communication” (or variationsthereof) refers to any manner and/or way in which functional unitsand/or modules, such as, but not limited to, computers, laptopcomputers, PDAs, modules, network servers, routers, gateways, and othertypes of hardware and/or software, may be in communication with eachother. Some non-limiting examples include: (i) activating or invokinganother such functional unit or module, and (ii) sending, and/orreceiving data or metadata via: a network, a wireless network, software,instructions, circuitry, phone lines, Internet lines, satellite signals,electric signals, optical signals, electrical and magnetic fields and/orpulses, and/or so forth.

Unless stated or clearly implied otherwise, network communication inaccordance with the present disclosure may be accomplished through anysuitable communication channels, such as, for example, a telephonenetwork, an extranet, an intranet, Internet, point of interaction device(point of sale device, personal digital assistant, cellular phone,kiosk, etc.), online network communications, wireless communications,local area network (LAN), wide area network (WAN), networked or linkeddevices and/or the like. Moreover, although the network communicationsmay be implemented with TCP/IP communications protocols, suchcommunications may also be implemented using IPX, Appletalk, IP-6,NetBIOS, OSI or any number of existing or future protocols. Specificinformation related to the protocols, standards, and applicationsoftware utilized in connection with the Internet is generally known tothose skilled in the art and, as such, need not be detailed herein. See,for example, DILIP NAIK, INTERNET STANDARDS AND PROTOCOLS (1998); JAVA 2COMPLETE, various authors, (Sybex 1999); DEBORAH RAY AND ERIC RAY,MASTERING HTML 4.0 (1997); and LOSHIN, TCP/IP CLEARLY EXPLAINED (1997),the contents of which are hereby incorporated by reference.

For the computational instructions (e.g., software, scripts, firmware,etc.) and/or associated data disclosed or required due to the functionalunits or modules described herein, it is within the scope of the presentdisclosure to explicitly include storage media for storing suchinstructions and/or data utilized in enabling the system(s) andmethod(s) disclosed herein. For example, such storage media may be:computer readable magnetic disks or tape, optical disks, and othernon-volatile or non-transient transportable memory (e.g., USB memorysticks, etc.).

As used herein, “comprising,” “including,” “containing,” “is,” “are,”“characterized by,” and grammatical equivalents thereof are inclusive oropen-ended terms that do not exclude additional unrecited elements ormethod steps unless explicitly stated otherwise. “Comprising” is to beinterpreted as including the more restrictive terms “consisting of” and“consisting essentially of.”

Description of the Figures and Operation of the Distributed Image/VideoProcessing System.

FIG. 1 shows a distributed image/video processing system 10 whichincludes a plurality of camera/video recorders 20 operatively connectedto a communications network 24 (e.g., the Internet) for transmittingimage/video related data to the image/video capture site 28. Each of thecamera/video recorders 20 may be one a substantially single purposedevice such as a standalone camera or video recorder, or may be amulti-purpose device which includes a mobile (wireless) phone such as asmart phone, a computer laptop/tablet, or other computational networkedcommunications device (e.g., a special purpose wireless communicationsdevice for transmitting images from a robot). Moreover, the camera/videorecorders 20 are typically generate, store and process images/videos asdigital data as one skilled in the art will understand. Instead of thenetwork 24 being the Internet, other communications networks are alsowithin the scope of the present disclosure such as local area (wireless)networks (as, e.g., provided in hospitals and institutions of highereducation) or private wide area virtual networks. The image/videocapture network site 28 may be an Internet website or any other networksite accessible and known to the camera/video recorders 20.

A representative high level internal structure of each of thecamera/video recorders 20 is shown by the upper left-hand camera/videorecorder 20 of FIG. 1. In particular, each such recorder 20 includes animage/video generator 32 that, e.g., generates digital image datacorresponding to a scene whose image(s) are captured. Such a generator32 may be charge coupled device, a digital camera or video recorder, orCMOS sensors, cell phones, PC cameras, CMOS cameras and tablet cameras.Each of the camera/video recorders 20 further include a compressor 36that can be used to compress such digital image data by the generator32. There are a large number of image data compression techniques thatmay be embodied within the compressor 36, including both lossy andlossless data compression techniques. The following data compressiontechniques are representative as one of skill in the art willunderstand:

For Digital Images (Photos):

-   -   Cartesian Perceptual Compression: Also known as CPC, is a        proprietary image file format. It was designed for high        compression of black-and-white raster Document Imaging for        archival scans.    -   DjVu: This is a computer file format designed primarily to store        scanned documents, especially those containing a combination of        text, line drawings, and photographs. It uses technologies such        as image layer separation of text and background/images,        progressive loading, arithmetic coding, and lossy compression        for bitonal (monochrome) images. This allows for high-quality,        readable images to be stored in a minimum of space, so that they        can be made available on the web.    -   Fractal compression: This is a lossy compression method for        digital images, based on fractals. The method is best suited for        textures and natural images, relying on the fact that parts of        an image often resemble other parts of the same image. Fractal        algorithms convert these parts into mathematical data called        “fractal codes” which are used to recreate the encoded image.    -   HAM: This is a hardware compression of color information used in        Amiga computers,    -   ICER: This is compression method is used by the Mars Rovers:        related to JPEG 2000 in its use of wavelets,    -   JPEG: In computing, JPEG is a commonly used method of lossy        compression for digital photography (image). The degree of        compression can be adjusted, allowing a selectable tradeoff        between storage size and image quality. JPEG typically achieves        10:1 compression with little perceptible loss in image quality.        JPEG compression is used in a number of image file formats.        JPEG/Exif is the most common image format used by digital        cameras and other photographic image capture devices; along with        JPEG/JFIF, it is the most common format for storing and        transmitting photographic images on the World Wide Web. These        format variations are often not distinguished, and are simply        called JPEG.    -   JPEG 2000: This is an image compression standard and coding        system. It was created by the Joint Photographic Experts Group        committee in 2000 with the intention of superseding their        original discrete cosine transform-based JPEG standard (created        in 1992) with a newly designed, wavelet-based method. JPEG        2000's format can be used for both lossy or lossless        compression,    -   JBIG2: This is an image compression standard for bi-level        images, developed by the Joint Bi-level Image Experts Group. It        is suitable for both lossless and lossy compression.    -   PGF (Progressive Graphics File): This compression method can be        lossless or lossy. PGF is a wavelet-based bitmapped image format        that employs lossless and lossy data compression. PGF was        created to improve upon and replace the JPEG format.    -   Wavelet compression: This is a form of data compression well        suited for image compression (sometimes also video compression        and audio compression). Notable implementations are JPEG 2000        and ECW for still images, and REDCODE, the BBC's Dirac, and Ogg        Tarkin for video. The goal is to store image data in as little        space as possible in a file. Wavelet compression can be either        lossless or lossy.    -   S3 Texture Compression (S3TC) (sometimes also called DXTn or        DXTC): This is a group of related lossy texture compression        algorithms originally developed by Iourcha et al. of S3        Graphics, Ltd.^([1]) for use in their Savage 3D computer        graphics accelerator. The method of compression is strikingly        similar to the previously published Color Cell        Compression,^([2]) which is in turn an adaptation of Block        Truncation Coding published in the late 1970s. Unlike some image        compression algorithms (e.g. JPEG), S3TC's fixed-rate data        compression coupled with the single memory access (cf. Color        Cell Compression and some VQ-based schemes) made it ideally        suited for use in compressing textures in hardware accelerated        3D computer graphics. Its subsequent inclusion in Microsoft's        DirectX 6.0 and OpenGL 1.3 (GL_ARB_texture_compression) led to        widespread adoption of the technology among hardware and        software makers. While S3 Graphics is no longer a leading        competitor in the graphics accelerator market, license fees are        still levied and collected for the use of S3TC technology, for        example in game consoles and graphics cards. The inclusion of        patented technology within OpenGL and its wide usage in software        have led to a requirement for the driver to support it and        present a major block within open source AMD and Intel driver        stack on Linux.        For Video Data:    -   DV: DV is an intraframe video compression scheme, which uses the        discrete cosine transform (DCT) to compress video on a        frame-by-frame basis. Audio is stored uncompressed.    -   H.263: This is a video compression standard originally designed        as a low-bitrate compressed format for videoconferencing. It was        developed by the ITU-T Video Coding Experts Group (VCEG) in a        project ending in 1995/1996 as one member of the H.26× family of        video coding standards in the domain of the ITU-T.        -   H.263 has since found many applications on the internet:            much Flash Video content (as used on sites such as YouTube,            Google Video, MySpace, etc.) used to be encoded in Sorenson            Spark format (an incomplete implementation of            H.263^([1][2][3])), though many sites now use VP6 or H.264            encoding. The original version of the RealVideo codec was            based on H.263 up until the release of RealVideo 8.        -   H.263 is a required video codec in ETSI 3GPP technical            specifications for IP Multimedia Subsystem (IMS), Multimedia            Messaging Service (MMS) and Transparent end-to-end            Packet-switched Streaming Service (PSS). In 3GPP            specifications, H.263 video is usually used in 3GP container            format.    -   The codec was first designed to be utilized in H.324 based        systems (PSTN and other circuit-switched network        videoconferencing and videotelephony), but has since also found        use in H.323 (RTP/IP-based videoconferencing), H.320 (ISDN-based        videoconferencing), RTSP (streaming media) and SIP (Internet        conferencing) solutions.        -   H.263 was developed as an evolutionary improvement based on            experience from H.261, the previous ITU-T standard for video            compression, and the MPEG-1 and MPEG-2 standards. Its first            version was completed in 1995 and provided a suitable            replacement for H.261 at all bitrates. It was further            enhanced in projects known as H.263v2 (also known as H.263+            or H.263 1998), MPEG-4 Part 2 and H.263v3 (also known as            H.263++ or H.263 2000). MPEG-4 Part 2 is H.263 compatible in            the sense that a basic H.263 bitstream is correctly decoded            by an MPEG-4 Video decoder.        -   The next enhanced codec developed by ITU-T VCEG (in            partnership with MPEG) after H.263 is the H.264 standard,            also known as AVC and MPEG-4 part 10. As H.264 provides a            significant improvement in capability beyond H.263, the            H.263 standard is now considered a legacy design. Most new            videoconferencing products now include H.264 as well as            H.263 and H.261 capabilities.        -   H.264/MPEG-4 Part 10 or AVC (Advanced Video Coding): This is            a standard for video compression, and is currently one of            the most commonly used formats for the recording,            compression, and distribution of high definition video. The            final drafting work on the first version of the standard was            completed in May 2003.        -   H.264/MPEG-4 AVC is a block-oriented            motion-compensation-based codec standard developed by the            ITU-T Video Coding Experts Group (VCEG) together with the            International Organization for Standardization            (ISO)/International Electrotechnical Commission (IEC) Moving            Picture Experts Group (MPEG). It was the product of a            partnership effort known as the Joint Video Team (JVT). The            ITU-T H.264 standard and the ISO/IEC MPEG-4 AVC standard            (formally, ISO/IEC 14496-10-MPEG-4 Part 10, Advanced Video            Coding) are jointly maintained so that they have identical            technical content.        -   H.264 is perhaps best known as being one of the codec            standards for Blu-ray Discs; all Blu-ray Disc players must            be able to decode H.264. It is also widely used by streaming            internet sources, such as videos from Vimeo, YouTube, and            the iTunes Store, web software such as the Adobe Flash            Player and Microsoft Silverlight, broadcast services for DVB            and SBTVD, direct-broadcast satellite television services,            cable television services, and real-time videoconferencing.    -   Motion JPEG (variations thereof): This is a compression method        that uses a lossy form of intraframe compression based on the        discrete cosine transform (DCT). This mathematical operation        converts each frame/field of the video source from the time        domain into the frequency domain (aka transform domain). A        perceptual model based loosely on the human psychovisual system        discards high-frequency information, i.e. sharp transitions in        intensity, and color hue. In the transform domain, the process        of reducing information is called quantization. In laymen's        terms, quantization is a method for optimally reducing a large        number scale (with different occurrences of each number) into a        smaller one, and the transform-domain is a convenient        representation of the image because the high-frequency        coefficients, which contribute less to the over picture than        other coefficients, are characteristically small-values with        high compressibility. The quantized coefficients are then        sequenced and losslessly packed into the output bitstream.        Nearly all software implementations of M-JPEG permit user        control over the compression-ratio (as well as other optional        parameters), allowing the user to trade off picture-quality for        smaller file size. In embedded applications (such as miniDV,        which uses a similar DCT-compression scheme), the parameters are        pre-selected and fixed for the application.        -   M-JPEG is an intraframe-only compression scheme (compared            with the more computationally intensive technique of            interframe prediction). Whereas modern interframe video            formats, such as MPEG1, MPEG2 and H.264/MPEG-4 AVC, achieve            real-world compression-ratios of 1:50 or better, M-JPEG's            lack of interframe prediction limits its efficiency to 1:20            or lower, depending on the tolerance to spatial artifacting            in the compressed output. Because frames are compressed            independently of one another, M-JPEG imposes lower            processing and memory requirements on hardware devices.        -   As a purely intraframe compression scheme, the image-quality            of M-JPEG is directly a function of each video frame's            static (spatial) complexity. Frames with large            smooth-transitions or monotone surfaces compress well, and            are more likely to hold their original detail with few            visible compression artifacts. Frames exhibiting complex            textures, fine curves and lines (such as writing on a            newspaper) are prone to exhibit DCT-artifacts such as            ringing, smudging, and macroblocking. M-JPEG            compressed-video is also insensitive to motion-complexity,            i.e. variation over time. It is neither hindered by highly            random motion (such as the surface-water turbulence in a            large waterfall), nor helped by the absence of motion (such            as static landscape shot by tripod), which are two opposite            extremes commonly used to test interframe video-formats.        -   For QuickTime formats, Apple has defined two types of            coding: MJPEG-A and MJPEG-B. MJPEG-B no longer retains valid            JPEG Interchange Files within it; hence it is not possible            to take a frame into a JPEG file without slightly modifying            the headers.    -   Ogg Theora: This is a free, open container format maintained by        the Xiph.Org Foundation. Ogg is designed to provide for        efficient streaming and manipulation of high quality digital        multimedia.        -   The Ogg container format can multiplex a number of            independent streams for audio, video, text (such as            subtitles), and metadata.        -   In the Ogg multimedia framework, Theora provides a lossy            video layer. The audio layer is most commonly provided by            the music-oriented Vorbis format but other options include            the human speech compression codec Speex, the lossless audio            compression codec FLAC, and OggPCM.    -   Dirac: Dirac employs wavelet compression, instead of the        discrete cosine transforms used in older compression formats.        Dirac applies wavelets to video compression.    -   VC-1: This is the informal name of the SMPTE 421M video codec        standard, which was initially developed as a proprietary video        format by Microsoft before it was released as a formal SMPTE        standard video format on Apr. 3, 2006. It is today a widely        supported standard found in HD DVDs, Blu-ray Discs, Windows        Media, Slingbox, and Microsoft's Silverlight framework.

Note that it is within the scope of the present disclosure for thecompressor 36 to include and utilize a plurality of digital image/videodata compression techniques.

The camera/video recorder 20 also includes various image/videoenhancement processes which are activated/controlled as appropriate by amanager 40. The image/video enhancement processes manager 40 formanaging the enhancement of the digital image/video data obtained fromthe generator 32 as one skilled in the art will understand. For example,the image/video enhancement processes manager 40 manages the processingthat can be performed by various de-noising techniques (shown asde-noising 42 processes in FIG. 1) may be used to reduce what isdetermined as noise in the image/video data. Such as:

-   -   Salt and pepper noise (sparse light and dark disturbances),        wherein pixels in the image/video are very different in color or        intensity from their surrounding pixels; the defining        characteristic is that the value of a noisy pixel bears no        relation to the color of surrounding pixels. Generally this type        of noise will only affect a small number of image pixels. When        viewed, the image contains dark and white dots, hence the term        salt and pepper noise. Typical sources include flecks of dust        inside the camera and overheated or faulty CCD elements.    -   Gaussian noise, wherein pixels in the image/video may be changed        from their original values by (usually) small amounts. In        Gaussian noise, it is assumed that the amount of distortion of a        pixel value plotted against the frequency, with which it occurs,        shows a normal distribution of noise.        Note that the noise at different pixels can be either correlated        or uncorrelated; in many cases, noise values at different pixels        are modeled as being independent and identically distributed,        and hence uncorrelated.

Additionally, various sharpening and unsharp masking techniques (shownas sharpening 44 processes in FIG. 1) may be managed (e.g., activated asappropriate) by the image/video enhancement processes manager 40 as oneskilled in the art will understand. Such sharpening and de-noisingtechniques are discussed hereinbelow. Additional enhancements include,e.g., white balancing as one skilled in the art will understand.

The camera/video recorder 20 also includes a network interface 46 forcommunicating with various sites on the network 24, such as theimage/video capture network site 28. Additionally, the camera/videorecorder 20 includes a transmission evaluator 48 which determines datarelated to one or more network transmission characteristics (e.g., anavailable bandwidth) of the network 24 for transmitting image/video datato the image/video capture site 28. The network transmission evaluator48 may determine such data related to available network bandwidth byreceiving information for one or more network transmissioncharacteristics, wherein such characteristics may be, e.g., a networktransmission time delay indicative of time delays when communicatingwith one or more network sites, a network data rate indicative of one ormore transmission data rates when communicating with one or more networksites, and a maximum transmission time delay threshold whencommunicating with predetermined network site (e.g., the site 28). Inorder to obtain such network transmission characteristics, varioustechniques may be used, including:

-   -   (i) Pinging the image/video capture site 28 and comparing, e.g.,        a running average of the time delay for pings with entries in a        data table (not shown) that correlates such ping time delay        information with a value indicative of available network 24        bandwidth available; in particular, such ping time delay is        inversely related to the available network bandwidth; and/or    -   (ii) Determining a data transmission rate of the network at the        recorder 20 or requesting a data transmission rate measurement        from the image/video capture site 28, wherein the greater the        measured data transmission rate, the greater the network        bandwidth available; and/or    -   (iii) Requesting a maximum transmission delay time threshold        from the network site 28, wherein this threshold is the maximum        transmission time delay threshold that the site 28 will wait for        digital image/video data to be received before timing out from        an initial corresponding network contact by the recorder 20 for        transmitting such data.

In an alternative/additional embodiment, the network transmissionevaluator 48 may ping a plurality of different network 24 sites fordetermining the extent of network traffic and thereby deduce a valueindicative of available network bandwidth. In another embodiment, thenetwork transmission evaluator 48 may request a network trafficmeasurement from the image/video capture site 28, wherein such ameasurement may be, e.g., correlated with the data rate being receivedby the network interface 50 of the image/video capture site 28, and/orone or more predetermined other network sites.

The camera/video recorder 20 further includes a controller 52 thatdetermines how image/video data is processed at the camera/videorecorder. In particular (and as described in more detail below withreference to FIG. 2), the controller determines the image/videoprocessing performed at the camera/video recorder 20 on image/videodata, wherein such processing is dependent on the current network 24 oneor more transmission characteristics (e.g., available bandwidth) fortransferring such image/video data to the image/video capture site 28.In particular, the controller 52 sets imaging/video parameters forcapturing, processing and transmitting (via the network 24) a largeramount of such data (e.g., containing more information content) whenthere is at least a first threshold of network 24 bandwidth available,and progressively lesser amounts of the such data as estimates ofnetwork bandwidth reduce. In at least one embodiment, the controller 52may select a compression technique, provided by the compressor 36, alongwith determining the image/video processing techniques to be performedthat are compatible with the compression technique. For example, oncethe network transmission evaluator 48 has provided information relatedto the network bandwidth available to the controller 52, this controllermay first determine a compression technique provided by the compressor36. However, since certain image/video enhancing techniques are notcompatible with certain compression techniques (as is further describedhereinbelow), the controller 52 may also determine one or moreimage/video processing techniques to be performed prior to the datacompression (by the determined compression technique) wherein suchimage/video processing techniques are compatible with the compressiontechnique.

Referring to the image/video capture network site 28, in addition to thenetwork interface 44, this site includes decompressor module 60 fordecompressing compressed image/video data received from the camera/videorecorders 20. The decompressor 60 includes one or more (in at least someembodiments, preferably a plurality of) complementary modules providingdata decompression techniques to the compression techniques availableand used at the camera/video recorders 20 as one skilled in the art willunderstand. The network site 28 also includes one or more (generally aplurality) of image/video enhancement processes (e.g., de-noising 68 andsharpening 72) as well as a manager 64 for managing the processes forenhancing the decompressed image/video data. For example, the manager 64may sequentially activate the enhancement processes for, e.g.,pipelining therebetween as determined by instructions received from thecontroller 76, and store the resulting enhanced image/video data in theimage/video archive 84.

Examples of the enhancement processes resident on both the recorders 20and the network site 28 are as follows:

-   -   (a) One or more de-noising (noise reduction) processes 42 and 68        for de-noising the decompressed data. De-noising is very helpful        in making digital image/video data more homogenous (e.g., fewer        pixels having extreme outlier values in comparison to        surrounding pixels). For instance, de-noising removes high        frequency pixel data (i.e., pixel data which is Light Defective        Pixel-DN count (110-140) using a light grey chart (0.44 Neutral        Macbeth). Dark Defecctive Pixel-DN count (0-10) using a dark        black chart (1.5 Black Macbeth) that may or may not be desirable        in the resulting image/video. Additionally, de-noising also        provides correction for what is called in the art as “defect        pixel correction” wherein such de-noising removes        dead/weak/strong pixels that are simply bad due to the digital        image/video data generation process (e.g., in the generator 32).        Such de-noising processes may utilize various de-noising        techniques some of which are described as follows.        -   Chroma and Luminance Noise Separation:            -   In real-world photographs, the highest spatial-frequency                detail consists mostly of variations in brightness                (“luminance detail”) rather than variations in hue                (“chroma detail”). Since any noise reduction algorithm                should attempt to remove noise without sacrificing real                detail from the scene photographed, one risks a greater                loss of detail from luminance noise reduction than                chroma noise reduction simply because most scenes have                little high frequency chroma detail to begin with. In                addition, most people find chroma noise in images more                objectionable than luminance noise; the colored blobs                are considered “digital-looking” and unnatural, compared                to the grainy appearance of luminance noise that some                compare to film grain. For these two reasons, most                photographic noise reduction algorithms split the image                detail into chroma and luminance components and apply                more noise reduction to the former. Most dedicated                noise-reduction computer software allows the user to                control chroma and luminance noise reduction separately.        -   Linear Smoothing Filters:            -   One method to remove noise is by convolving the original                image with a mask that represents a low-pass filter or                smoothing operation as one skilled in the art will                understand. Such convolution brings the value of each                pixel into closer harmony with the values of its                neighbors. In general, a smoothing filter sets each                pixel to the average value, or a weighted average, of                itself and its nearby neighbors; a Gaussian filter is                just one possible set of weights.            -   Smoothing filters tend to blur an image, because pixel                intensity values that are significantly higher or lower                than the surrounding neighborhood “smear” across the                area. Because of this blurring, linear filters are                seldom used in practice for noise reduction; they are,                however, often used as the basis for nonlinear noise                reduction filters.        -   Anisotropic Diffusion:            -   Anisotropic diffusion is a method for removing noise                which evolves the image/video under a smoothing partial                differential equation similar to the heat equation which                is called anisotropic diffusion. With a spatially                constant diffusion coefficient, this is equivalent to                the heat equation or linear Gaussian filtering, but with                a diffusion coefficient designed to detect edges, the                noise can be removed without blurring the edges of the                image.        -   Nonlinear Filters:            -   A median filter is an example of a non-linear filter                and, if properly designed, is very good at preserving                image detail. To run a median filter:            -   1. Consider each pixel in the image;            -   2. Sort the neighboring pixels into order based upon                their intensities; and            -   3. Replace the original value of the pixel with the                median value from the list.        -   A median filter is a rank-selection (RS) filter, a            particularly harsh member of the family of rank-conditioned            rank-selection (RCRS) filters; a much milder member of that            family, for example one that selects the closest of the            neighboring values when a pixel's value is external in its            neighborhood, and leaves it unchanged otherwise, is            sometimes preferred, especially in photographic            applications.            -   Median and other RCRS filters are good at removing salt                and pepper noise from an image, and also cause                relatively little blurring of edges, and hence are often                used in computer vision applications.    -   In selecting a noise reduction technique(s) 68 (also referred to        as a “de-noising technique), several factors may be taken into        account:        -   the available computer power and time available: a digital            camera must apply noise reduction in a fraction of a second            using a tiny onboard CPU, while a desktop computer has much            more power and time        -   whether sacrificing some actual image/video detail is            acceptable if it allows more noise to be removed (how            aggressively to decide whether variations in the image are            noise or not)        -   the characteristics of the noise and the detail in the            image/video, to better make those decisions.    -   (b) One or more sharpening and unsharp masking processes 44 and        72 for sharpening the decompressed data, wherein such processes        may utilize various techniques some of which are now described.        -   Deconvolution:            -   In optics and imaging, the term “deconvolution” is                specifically used to refer to the process of reversing                the optical distortion that takes place in an optical                microscope, electron microscope, telescope, or other                imaging instrument, thus creating clearer images. It is                usually done in the digital domain by a software                algorithm, as part of a suite of microscope image                processing techniques. Deconvolution is also practical                to sharpen images that suffer from fast motion or                jiggles during capturing.            -   The usual method is to assume that the optical path                through the instrument is optically perfect, convolved                with a point spread function (PSF), that is, a                mathematical function that describes the distortion in                terms of the pathway a theoretical point source of light                (or other waves) takes through the instrument. Usually,                such a point source contributes a small area of                fuzziness to the final image. If this function can be                determined, it is then a matter of computing its inverse                or complementary function, and convolving the acquired                image with that. The result is the original, undistorted                image.            -   In practice, finding the true PSF is impossible, and                usually an approximation of it is used, theoretically                calculated or based on some experimental estimation by                using known probes. Real optics may also have different                PSFs at different focal and spatial locations, and the                PSF may be non-linear. The accuracy of the approximation                of the PSF will dictate the final result. Different                algorithms can be employed to give better results, at                the price of being more computationally intensive. Since                the original convolution discards data, some algorithms                use additional data acquired at nearby focal points to                make up some of the lost information. Regularization in                iterative algorithms (as in expectation-maximization                algorithms) can be applied to avoid unrealistic                solutions.            -   When the PSF is unknown, it may be possible to deduce it                by systematically trying different possible PSFs and                assessing whether the image has improved. This procedure                is called blind deconvolution. Blind deconvolution is a                well-established image restoration technique in                astronomy, where the point nature of the objects                photographed exposes the PSF thus making it more                feasible. It is also used in fluorescence microscopy for                image restoration, and in fluorescence spectral imaging                for spectral separation of multiple unknown                fluorophores. The most common iterative algorithm for                the purpose is the Richardson-Lucy deconvolution                algorithm; the Wiener deconvolution (and approximations                thereof) is/are the most common non-iterative                algorithms.        -   Digital Unsharp Masking:            -   Unsharp masking applies a Gaussian blur to a copy of the                original image and then digitally compares it to the                original. If the difference is greater than a                user-specified threshold setting, the images are (in                effect) subtracted. The threshold control constrains                sharpening to image elements that differ from each other                above a certain size threshold, so that sharpening of                small image details, such as photographic grain, can be                suppressed.            -   Digital unsharp masking is a flexible and powerful way                to increase sharpness, especially in scanned images.                However, it is easy to create unwanted and conspicuous                edge effects, or increase image noise. On the other                hand, these effects can be used creatively, especially                if a single channel of an RGB or Lab image is sharpened.                Undesired effects can be reduced by using a                mask—particularly one created by edge detection—to only                apply sharpening to desired regions, sometimes termed                “smart sharpen”.            -   Typically three settings (known as “amount”, “radius”,                and “threshold”) control digital unsharp masking:            -   Amount is listed as a percentage, and controls the                magnitude of each overshoot (how much darker and how                much lighter the edge borders become). This can also be                thought of as how much contrast is added at the edges.                It does not affect the width of the edge rims.            -   Radius affects the size of the edges to be enhanced or                how wide the edge rims become, so a smaller radius                enhances smaller-scale detail. Higher Radius values can                cause halos at the edges, a detectable faint light rim                around objects. Fine detail needs a smaller Radius.                Radius and Amount interact; reducing one allows more of                the other.            -   Threshold controls the minimum brightness change that                will be sharpened or how far apart adjacent tonal values                have to be before the filter does anything. This lack of                action is important to prevent smooth areas from                becoming speckled. The threshold setting can be used to                sharpen more-pronounced edges, while leaving subtler                edges untouched. Low values should sharpen more because                fewer areas are excluded. Higher threshold values                exclude areas of lower contrast.                -   Various recommendations exist as to good starting                    values for these parameters.            -   Generally a radius of 0.5 to 2 pixels and an amount of                50-150% is a reasonable start.

As with the camera/video recorder 20, the image/video capture networksite 28 also includes a controller (76) for controlling the processingof the image/video data (compressed, enhanced and/or other techniques)from one of the plurality of camera/video recorders 20. In particular,the controller 76 controls the processing of such image/video data sothat it is appropriately decompressed (as necessary by the decompressor60) and appropriately enhanced (as necessary by the image/videoenhancement processes manager 64). Additionally, the site 28 may alsoinclude a temporary (non-transient) image/video data storage 80 fortemporary storage prior to processing. Note that for each transmissionof image/video data (whether compressed, enhanced or otherwise), suchdata is associated in the data storage 80 with: (i) such data'scorresponding processing history data also transmitted to the site 28,and (ii) an identifier identifying the owner or user of the camera/videorecorder 20 from which the original image/video data was generated.Thus, for each transmission of image/video data, the controller 76 mayretrieve from the data storage 80 the corresponding processing historydata for determining, e.g., how to decompress the image/video data, andhow to enhance the image/video data. In directing such processing, thecontroller 76 may examine a quality field and/or one or more instructionfields in the corresponding processing history data for determining whatenhancement to the image/video data are to be performed. Subsequently,once an instance of the image/video data is fully processed, theresulting image/video data is stored in the image/video archive 84,wherein it may be, e.g., retrieved and displayed by the correspondinguser whose identity is associated with the instance.

System Operation.

In the description hereinbelow, various terms are bolded and italicizedto identify such terms as being more fully described/defined in Appendixprovided hereinbelow.

During operation, when digital image/video data is generated by thegenerator 32, the controller 52 determines (prior to transmitting suchdigital image/video data to the image/video capture site 28): (i) theimage/video enhancement processes 40 (if any) to apply to the digitalimage data, and (ii) how such data (if any) is subsequently processed bythe compressor 36 after the enhancement processes are applied. Inparticular, upon the controller 52 receiving, from the networktransmission evaluator 48, data indicative of the (current) network 24bandwidth available for transmission of the digital image data (or acompressed and/or enhanced version thereof), this controller determinesthe image/video enhancement processes such as a de-noising process 42 ora sharpening process 44 to activate (descriptions of such enhancementprocesses being described hereinabove). Thus, the greater networkbandwidth available, the less compression is applied, and as theavailable network bandwidth reduces, the more data compression may beapplied to the digital image/video data (or an enhanced versionthereof). Moreover, as discussed hereinabove, the data compressiontechnique and the image/video enhancement processes may beselected/determined by the controller 52 so that they are compatiblewith one another, e.g., in the sense that the resulting compressed datawill provide an appropriate image/video presentation once processed atthe network site 28 (for example, it is undesirable for the finalimage/video to have blank scenes therein such as “green screens” as oneskilled in the art will understand).

Subsequently, upon the image/video capture network site 28 receiving (atthe network interface 50) the compressed image/video data from thecamera/video recorder 20, this network interface notifies the controller76 so that the controller 76 can provide instructions for processing thedata in consideration of the corresponding processing history data.

In general for video data, if the network 24 bandwidth available is high(e.g., “High Bandwidth” in Tables 1B and 1C below for video data), itmay be preferable to perform: (i) Aggressive de-noising, and (ii)correspondingly Little/no Compression. This is due to the fact thatde-noising and compression techniques are many times performing similarfunctions when it comes to the removal of high frequency pixel data invideo data. For example, inter-frame blocked based compressionalgorithms like MPEG (and variations thereof, e.g., MPEG1, MPEG2 andMPEG4), H.264, VC-1, Flash, etc.) remove high frequency pixel data toachieve more compression as one skilled in the art will understand.Additionally, de-noising generally also removes such high frequencypixel data thereby making videos more homogenous as describedhereinabove. Thus, if de-noised data is provided to such inter-frameblocked based compression algorithms, such algorithms may likely removethe next highest pixel frequency data. In some cases, the resultingvideo may be appear washed out, or blank with no picture at all in theworst-case. Thus, when Little/no Compression is applied to video data(e.g., when there is high available network 24 bandwidth), Aggressivede-noising may be preferable for at least the removal of high frequencypixel data.

However, when the network 24 available bandwidth is low (e.g., “LowBandwidth” in Tables 1B and 1C below for video data), and a potentiallyhigh compression process (of the compressor 36) is activated to performAggressive Compression (or Extremely Aggressive Compression), then sincesuch compression will both highly compress the video data and alsoremove high frequency pixel data, Little/no de-noising is preferableprior to compression thus leaving noise (and high frequency pixel data)in the video data.

Regarding sharpening, if Aggressive sharpening is performed on animage/video, high frequency pixel data may likely be created. Such highfrequency pixel data is beneficial when the aggressively sharpened videodata is subsequently compressed by, e.g., an inter-frame block basedalgorithm since such an algorithm will remove the high frequency pixeldata. In particular, the sharpening and compression processeseffectively cancel out one another in this regard, but the result alsohas a reduced image/video data size. Accordingly, sharpening andcompression may be directly related with one another in the recorder 20,and it may be necessary for the controller 52 to take such interactionsinto account in determining the combination of data compression withimage/video processing techniques. Thus, in at least some cases,sharpening of digital image/video data may be based on a selectedcompression technique to be used. Alternatively, the compressiontechnique may be based on a selected sharpening technique to be used.

For instance, for the M-JPEG compression technique, an overly sharpimage (i.e., an image is “overly sharp” when ringing occurs as indicatedhereinabove) may be problematic since such ringing may not be removed bythis compression technique, even when Aggressive Compression orExtremely Aggressive Compression is performed. However, forH.264/MPEG4/VC-1 compression techniques, an overly sharp image may bepreferred when Aggressive Compression or Extremely AggressiveCompression is performed since high frequency pixels are removed by suchaggressive compression techniques.

In various embodiments, when the network 24 available bandwidth isabove, e.g., 536 Kbps (kilo bits per second, “High Bandwidth” in Table1A below) for images and 50,000 Kbps (“High Bandwidth” in Table 1Cbelow) for video, Little/no Compression of the digital image/video datamay be performed prior to network 24 transmission, and Little/nosharpening may be performed at the camera/video recorder 20. However,for less network 24 available bandwidth, more compression is performed(e.g., Moderate Compression or Aggressive Compression), and (i) morede-noising is performed for image (photo) data and (ii) less de-noisingis performed for video data. Additionally, as available networkbandwidth reduces, fewer other enhancement processes such as sharpeningand white balance are performed regardless of whether video or imagedata is generated at the recorder 20.

TABLES 1A through 1F hereinbelow show representative ranges or extentsfor available network bandwidth (in the leftmost two columns), and foreach such range or extent, it's table row shows the correspondingcompression, de-noising and sharpening that may be performed at therecorder 20 prior to transmission of the recorder processed image/videodata to the network site 28. Note that the bandwidth ranges or extentsin the leftmost two columns of TABLES 1A-1F are representative of one ormore of (a) a network pinging value(s), or a network data transmissionrate(s) as described hereinabove in describing the transmissionevaluator 48, and/or (b) a maximum time for image/video data transfer toa network subsystem (e.g., a website). Regarding such a maximum time fordata transfer, in one embodiment, the longer this maximum time, the lesspresumed network 24 available bandwidth is available. Accordingly, suchmaximum delay time and available network may be inversely related. Thus,in determining what image/video processing is performed at the recorder20, a current (or most recently obtained) measurement of the availablenetwork 24 bandwidth (or information indicative thereof) may be comparedto various predetermined bandwidth related information (e.g., bandwidthranges or extents, or maximum transmission time) known to the evaluator48 (e.g., those of the leftmost column of the TABLES 1A-1F). Forexample, the evaluator 48 may determine which of the bandwidth ranges orextents (as provided in at least one of the two leftmost columns ofTABLES 1A-1F hereinbelow) a current measurement of network 24 availablebandwidth would be classified. Subsequently, the controller 52 may usesuch a classification of the measurement to determine the degree of datacompression and image/video enhancement processes to perform asidentified in the same row of TABLES 1A-1F that identifies themeasurement's classification.

Note that there may also be a minimum time delay communicated to therecorder 20 as well. In particular, when the network 24 (or the networksite 28) is experiencing an overload condition, such a minimum timedelay may be communicated to the recorder 20 for purposely delaying atransmission of digital image/video data. When such a minimum time delayis provided to the recorder 20, the recorder 20 may perform additionalimage/video enhancement processes 64 prior to data compression via thecompressor 36.

For image data (not video), the following TABLE 1A is representative,wherein there is a maximum network 24 transfer delay time of 60 seconds,and a pixel is 3 bytes (RGB) uncompressed.

TABLE 1A Bandwidth Available Network Description Bandwidth RangeCompression De-noising Sharpening High At or above 536 kilo Nocompression Little/no Little/no Bandwidth bits/sec (kbps) (The imagedata may be de-noising sharpening. approximately 4,000 KB (kilobytes).)Moderate From below 536 kilo Moderate compression via, e.g., forModerate Moderate Bandwidth bits/sec (kbps) down compressing the imagedata to de-noising sharpening. to 402 kbps approximately 3,000 KB(kilobytes). Moderate From below 402 kbps Moderate compression via,e.g., for Moderate Moderate Bandwidth down to 268 kbps compressing theimage data to de-noising sharpening. approximately 2,000 KB (kilobytes).Low From below 268 kbps Aggressive compression via, e.g., for ModerateAggressive Bandwidth down to 134 kbps. compressing the image data tode-noising sharpening. approximately 1,000 KB (kilobytes). Low Frombelow 134 kbps Aggressive compression via, e.g., for AggressiveAggressive Bandwidth down to 67 kbps. compressing the image data tode-noising sharpening. approximately 1,000 KB (kilobytes).

For video data having 640×480 pixels per frame (compressed viaMPEG-4/H.264/VC-1/Flash and other inter-frame blocked based compressionalgorithms), the following TABLE 1B is representative. Note thatInternet video currently is generally transmitted at about 640×480pixels per frame (VGA), but may extend to, e.g., 1920×1080 pixels perframe (1080P).

TABLE 1B Bandwidth Available Network Description Bandwidth RangeCompression De-noising Sharpening High At or above 2,500 No compressionAggressive Little/No Bandwidth kilo bits/sec (kbps) de-noisingsharpening Moderate From below 2,500 Moderate compression. AggressiveLittle/No Bandwidth kilo bits/sec (kbps) de-noising sharpening down to1,500 kbps Moderate From below 1,500 kbps Moderate compression. ModerateModerate Bandwidth down to 768 kbps de-noising sharpening Moderate Frombelow 768 kbps Aggressive compression. Moderate Moderate Bandwidth downto 512 kbps de-noising sharpening Low From below 512 kbps Aggressivecompression. Moderate Aggressive Bandwidth down to 256 kbps de-noisingsharpening Low From below 256 kbps Aggressive compression. Little/NoneAggressive Bandwidth de-noising sharpening

For M-JPEG video data having 640×480 pixels per frame and VGA images,the following TABLE 1C is representative.

TABLE 1C Bandwidth Available Network Description Bandwidth RangeCompression De-noising Sharpening High At or above 50,000 No compressionAggressive Little/No Bandwidth kilo bits/sec (kbps) de-noisingsharpening Moderate From below 50,000 kbps Moderate compression.Aggressive Little/No Bandwidth down to 25,000 kbps de-noising sharpeningLow From below 25,000 kbps Aggressive compression. Aggressive ModerateBandwidth down to 10,000 kbps de-noising sharpening Low From below10,000 kbps Aggressive compression. Moderate Moderate Bandwidthde-noising sharpening

For embodiments where a 5 Mega-Pixel image is output by the generator32, and a corresponding image is to be transmitted over the Internet in20 seconds, such that white balance is performed manually by the user,exposure is automatic (with limits, e.g., 1/15 second), and both focusand zoom can be any appropriate user desired values, the following Table1D shows representative relationships between available bandwidth,compression, de-noising, and sharpening. Note, the numerical value “x”in each of the “Compression Factor” column cells means that theresulting data size is 1/x of the original size.

TABLE 1D Available Image Time to Compression Bandwidth bandwidth Sizecompression Send (in Factor & De- Description (Kbps) (Kb) type seconds)Description noising Sharpening High 5000+ 5000 Loss Less 20  2 Little/noLittle/no Bandwidth (Little/no de-noising sharpening Compression)Moderate Less than 5000 Loss Less 20  4 Moderate Moderate Bandwidth 5000and (Little/no de-noising sharpening greater than Compression) 1500Moderate Less than 5000 JPEG 20  8 Moderate Moderate Bandwidth 1500 and(Little/no de-noising sharpening greater than Compression) 768 Low Lessthan 5000 JPEG 20  19 Moderate Aggressive Bandwidth 768 and (Moderatede-noising sharpening greater than Compression) 320 Low Less than 5000JPEG 20 120 Aggressive Aggressive Bandwidth 320 and (Extremelyde-noising sharpening greater than Aggressive 50 Compression)

For embodiments where a 640×480 video is transmitted over the Internetin real time, such that white balance is performed manually by the user,exposure is automatic (with limits, e.g., 1/30 second), focus is off,and zoom is manual, the following Table 1E shows representativerelationships between available bandwidth, compression, de-noising, andsharpening. Note, the numerical value “x” in each of the “CompressionFactor” column cells means that the resulting data size is 1/x of theoriginal size.

TABLE 1E Available Image Compression Bandwidth bandwidth Sizecompression Factor & De- Description (Kbps) (Kb) type Descriptionnoising Sharpening High 2500+ 144000 H.264  58 Aggressive Little/noBandwidth (Moderate de-noising sharpening Compression) Moderate Lessthan 144000 H.264  96 Moderate Moderate Bandwidth 2500 and (Moderatede-noising sharpening greater than Compression) 1500 Moderate Less than144000 H.264 188 Moderate Moderate Bandwidth 1500 and (Moderatede-noising sharpening greater than Compression) 768 Low Less than 768144000 H.264 282 Moderate Aggressive Bandwidth and greater (Aggressivede-noising sharpening than 512 Compression) Low Less than 512 144000H.264 563 Little/no Aggressive Bandwidth and greater (Extremelyde-noising sharpening than 256 Aggressive Compression)

For embodiments where a 720P video is transmitted over the Internet inreal time, such that white balance is performed manually by the user,exposure is automatic (with limits, e.g., 1/60 second), focus is off,and zoom is manual, the following Table 1F shows representativerelationships between available bandwidth, compression, de-noising, andsharpening. Note, the numerical value “x” in each of the “CompressionFactor” column cells means that the resulting data size is 1/x of theoriginal size.

TABLE 1F Available Compression Bandwidth bandwidth Image Sizecompression Factor & De- Description (Kbps) (Kb) type Descriptionnoising Sharpening High 100000+ 864000 M-JPEG  9 Aggressive Little/noBandwidth (Little/no de-noising sharpening Compression) Moderate Lessthan 864000 M-JPEG 18 Aggressive Moderate Bandwidth 100000 and (Moderatede-noising sharpening greater than Compression) 50000 Moderate Less than864000 M-JPEG 35 Aggressive Moderate Bandwidth 50000 and (Moderatede-noising sharpening greater than Compression) 25000 Low Less than864000 M-JPEG 87 Moderate Moderate Bandwidth 25000 and (Aggressivede-noising sharpening greater than Compression) 10000

FIG. 2 shows a flowchart illustrating the high level steps performed byat least one embodiment of the image/video processing in capture system10 of the present disclosure. In step 204, the controller 52 receives(upon request or periodically) data indicative of the currentlyavailable network 24 bandwidth (or one or more constraints ontransmission of image/video data, e.g., a constraint such as a minimumtransmission delay time). Accordingly, the term “network transmissiondata” is used hereinbelow (and abbreviated in FIG. 2 to“NTWK_TRANSMN_DATA”) to denote such network or network site relatedtransmission attributes (more particularly, constraints) that are usedin influencing digital image/video data processing at a recorder 20 sothat the network transmission of such digital image/video data to aparticular network site (28) is more effective. Accordingly, thecontroller 52 may maintain (in internal data storage, not shown) suchnetwork transmission data. In one embodiment, this data may includeestimated available kilobytes per second that can be timely transmittedto the network site 28. Alternatively/additionally, such data mayinclude a network 24 time delay for transmissions to the network site28. Other possibilities include a designated time window for networktransmission, or the like. In step 208, the controller 52 receives asignal or notification that the recorder 20 is about to receiveimage/video data (e.g., the user of the recorder activated the recorderfor obtaining an image or a video). Note that when the controller 52 isnotified (e.g., by such user input), the controller determines, in thecase the network transmission data including available network bandwidthdata, whether the most recently obtained measurement of the availablenetwork 24 bandwidth is, e.g., below or above at least one predeterminednetwork bandwidth threshold. If the measurement is above such athreshold, then image/video enhancing processes, e.g., auto-exposure,auto-white balance, and auto-focus may be available for activation,e.g., during image/video initial capture by the recorder 20.Alternatively, if the measurement is below such a threshold, then one ormore image/video enhancing processes such as auto-exposure, auto-whitebalance, and auto-focus may be prevented from being activated. Inparticular, in step 212, the controller 52 accesses, e.g., an internaldata table (not shown, in FIG. 1), for determining whether networktransmission data has been obtained that may affect image/video initialcapture. For instance, this internal data table may include informationindicating that the network 24 has a sufficiently currently reduced (orincreased) available bandwidth to warrant changing the image/videoprocessing performed by the recorder 20. Accordingly, if there is areduction in network 24 available bandwidth (e.g., as per the bandwidthdescription and measurement range, of e.g., the last row of anapplicable one of the Tables 1A through 1F hereinabove), then step 216may be performed wherein, in one embodiment, the controller 52determines and communicates to the generator 32 which image/videocapabilities to reduce or entirely inhibit (e.g., auto-exposure,auto-white balance, auto-focus, etc.) in order to reduce the quantity ofimage/video data captured.

Whether step 216 is performed or not, in step 220, the image/videogenerator 32 generates and stores image/video data obtained from, e.g.,a user operating the camera/video recorder 20. Note that in oneembodiment, the camera/video recorder 20 may operate without requiringmanual operation such as when such a recorder 20 is used forsurveillance or monitoring. Further note that the generator 32 mayinclude non-transient data storage (not shown in FIG. 1) for thegenerated image/video data. Alternatively, such non-transient datastorage may be external to the generator 32 as one skilled in the artwill understand.

Once the image/video data is obtained (e.g., stored in a non-transientdata storage of the recorder 20), step 224 is performed wherein thecontroller 52 determines an amount (if any) and type of data compressionto apply to the image/video data for reducing the quantity of datatransmitted on the network 24 when delivering this image/video data (ora corresponding version thereof) to the image/video capture site 28. Inparticular, the image/video data is compressed a greater (lesser) amountwhen the available network 24 when a network constraint such asavailable network bandwidth is reduced (increased) as illustrated inTables 1A through 1F hereinabove.

In at least one embodiment, in performing step 224 for image data, theevaluator 48 obtains or reads a first network 24 related parameter dataindicative of a preferred size of the image data for transferring on thenetwork 24. Since the size of the image output by the generator 32 isavailable to the recorder 20 (e.g., 5 MegaPixels as in Table 1D above),a compression factor can be computed (i.e., size of generator outputtedimage divided by preferred image size). Additionally/optionally, asecond parameter data indicating the data compression type to performmay be provided via being read from a network 24 transmission (e.g.,transmitted from the site 28), or, alternatively, the compression typemay be determined by the recorder 20 (e.g., the recorder may determinean available compression type that provides the desired compressionfactor and is the least lossy). Given such a compression factor, andcompression type (e.g., Loss Less, or JPEG), a table (such as Table 1D)resident at the recorder 20 can be accessed to determine correspondingenhancement processes (and parameters therefor) such as de-noising andsharpening processes to perform.

Note that similar determinations can be made for video data. Forexample, if the network 24 provides a preferred transmission data rate,then assuming the recorder 20 has access to the video data rate (e.g.,Kbps) being output by the generator 32, a video compression factor candetermined for corresponding transmissions on the network. Additionally,a compression type can be determined either from being read from anetwork 24 (or site 28) transmission, or, alternatively, the compressiontype may be determined by the recorder 20, wherein the recorder maydetermine an available compression type that provides the desiredcompression factor and is the least lossy.

Accordingly, assuming (i) the recorder 20 has access to one or more ofthe tables (or corresponding data structures) providing the informationof, e.g., one or more of Tables 1D 1F (or similar tables for other imagesizes and/or video network transmission data rates), and assuming (ii)the recorder 20 also has access to desired or preferred a image/videonetwork transmission attributes (e.g., size or data rate), then suchtables can be accessed by the recorder to determine at least the type ofde-noising, sharpening, and compression processes to be applied, as wellas the parameters for operably configuring each of these processes.Thus, even though much of the description herein and the flowchart ofFIG. 2 is illustrative of such processes being dependent upon availablenetwork bandwidth, other known or unknown constraints/conditions (e.g.,substantially unrelated to available network bandwidth) may be involvedin determining the desired or preferred a image/video networktransmission attributes.

Subsequently, in step 228, the controller 52 determines an amount orextent (if any) and type of de-noising to perform on the image/videodata, wherein for image (e.g., photo) data, a greater amount ofde-noising is performed when a greater amount of compression is to beperformed on the image/video data, and wherein for video data, theamount or degree of de-noising is inversely related to the amount ordegree of compression to be performed. Thus, e.g., for image data, aminimal amount of de-noising may be performed if the controller 52determines that no or little data compression is to be performed.

Subsequently, in step 232, the controller 52 determines an amount orextent (if any) and type that the image/video data is to be sharpened,wherein the amount or extent of the sharpening is directly related tothe amount or extent of compression of the image/video data. Thus, e.g.,a minimal amount of sharpening may be performed if the controller 52determines that a minimal amount data compression is to be performed onthe image/video data.

In step 236, the controller 52 issues instructions to the image/videoenhancement processes 40 for digitally enhancing the image/video dataaccording to the determinations made in steps 228 and 232. Inparticular, the de-noising module 42 and/or sharpening module 44 may beactivated to apply to the image/video data their respective processesaccording to the determinations made in steps 228 and 232. Note, that inone embodiment, the de-noising of the image/video data (if any) is firstperformed and the sharpening (if any) is performed on the image/videodata output from the de-noising process. Additionally, in one embodimentof the recorder 20, one or more of the auto-exposure, auto-whitebalance, and auto-focus may also be image/video processing enhancementutilities provided in the enhancement processes 40, and may be similarlyprocessed in the steps 232 and 236. For example, the controller 52 maydetermine an amount or extent to apply such utilities dependent upon thecurrently available network 40 bandwidth, wherein such utilities areapplied inversely to the currently available network bandwidth.

In step, 240, assuming data compression is to be performed, thecontroller 52 issues instructions to the compressor 60 to compress theresulting version of the image/video data output from the image/videoenhancement processes 40 according to the determinations in step 224 of“COMPRESSION_INFO” in FIG. 2. Note, in some contexts, no compression maybe performed on the image/video data since there may be, e.g.,sufficient network 24 bandwidth, transmission time, or a transmissionwindow may be sufficiently wide to transmit the image/video data withoutcompressing it. Additionally, in some contexts, if the network 24bandwidth (transmission time, or a transmission window) is sufficientlyreduced, none of the image/video enhancement processes 40 may beperformed, and accordingly the compressor module 60 may receive theoriginally obtained image/video data. Note that the instructions fromthe controller 52 to the compressor 60 can indicate from where thecompressor is to obtain its input as one skilled in the art willunderstand. The compressor 60 may output the compressed data to apredetermined data storage (not shown in FIG. 1) as one skilled in theart will understand.

In step 244, the controller 52 prepares a processing history of theprocessing that has been performed on original image/video data obtainedat the recorder 20, wherein this history identifies the following:

-   -   (i) whether the image/video data has been compressed;    -   (ii) if the image/video data has been compressed, an        identification of the compression technique used and the        compression parameters used;    -   (iii) the image/video enhancement utilities applied to the        image/video data and their corresponding parameters,        including: (a) the type of de-noising applied (if any) and the        parameters used, (b) the type of sharpening applied (if any) and        the corresponding parameters used, (c) whether auto-exposure was        performed and the (any) corresponding parameters therefor, (d)        whether auto-white balance was performed and the (any)        corresponding parameters therefor, and (e) whether auto-focus,        manual focus and/or a zoom distance was performed and the (any)        corresponding parameters therefor;    -   (iv) the image/video enhancement utilities that desirably or        preferably should have been applied (e.g., under optimal network        24 bandwidth conditions of high available bandwidth such as a        ping round trip delay of less than 0.5 seconds to the site 28).        Additionally, such history information may also include an        identification of the recorder 20, and/or an identification of a        user, subscriber, or owner of the recorder for, e.g.,        identifying who owns or has access to the corresponding        image/video data stored on the network site 28 after any further        image/video processing is performed and the result is stored in        the image/video archive 84. Note that the history information        may be output by the controller 52 to a predetermined data        storage location prior to network transmission, such data        storage not shown in FIG. 1.

For ease of description, the image/video data resulting from the stepshereinabove will be referred to as “recorder processed image/videodata”. Accordingly, in step 248, the controller 52 issues instructionsfor transmitting both the recorder processed image/video data and itscorresponding history information to the image/video capture networksite 28. Such instructions may be received by the network interface 46for directing this interface to access the data storage for each of therecorder processed image/video data and its corresponding historyinformation, and to transmit each to the network site 28. In particular,the history information may be transmitted within a bitstream that alsotransmits the recorder processed image/video data, or alternatively, thehistory information may be transmitted through a separate RTP/RTSPtransmission as one skilled in the art will understand. In analternative embodiment, the controller 52 may access both the storedrecorder processed image/video data and its corresponding historyinformation for inputting them to the network interface 46 together witha network 24 address for transmission to the site 28 (the addressidentifying this site).

Subsequently, in step 252, the network interface 50 of the image/videocapture site 28 receives both the recorder processed image/video dataand its corresponding history information transmitted from thecamera/video recorder 20. Upon receiving and identifying each of therecorder processed image/video data and its corresponding historyinformation, the network interface 50 may output them to the temporaryimage/video data storage 80, this storage being managed by a databasemanagement system such as a relational database management system as oneskilled in the art will understand. Note that such a database managementsystem may maintain various context values for identifying when both therecorder processed image/video data and its corresponding historyinformation have been stored therein.

After the controller 76 is notified by the network interface 50 (or theabove database management system) of the receipt of both the recorderprocessed image/video data and its corresponding history information, instep 256, this controller determines from the history informationwhether the recorder processed image/video data requires decompressing.If decompression is required, then in step 260, the controller 76 issuesinstructions to the decompressor 60 to decompress the recorder processedimage/video data stored in the temporary image/video data storage 80. Inone embodiment, the controller 76 provides the following informationwith the decompression instructions:

-   -   (a) data for accessing the recorder processed image/video data        in the temporary image/video data storage 80; and    -   (b) data for accessing the fields of the corresponding history        information that identify compression type and parameters used        in compressing the recorder processed image/video data.        As one skilled in the art will understand, other information        besides or in addition to (a) and (b) immediately above may be        provided to the decompressor 60. Moreover, in one embodiment,        the controller 76 may only notify the decompressor 60 of newly        received (and stored) recorder processed image/video data and        its corresponding history information, and subsequently, the        decompressor determines whether decompression is to be applied,        the type of decompression, and the parameters therefor. Note        that the decompressed image/video data output by the        decompressor 60 can be stored in the data storage 80 along with        descriptor data identifying it as decompressed.

For ease of description, and whether the image/video data isdecompressed or not in step 260, the resulting image/video data will bereferred to as “decompressed image/video data” hereinbelow.

After (any) decompression of the recorder processed image/video data, instep 264 the controller 76 determines from the corresponding storedhistory data (any) enhancements to be performed on the decompressedimage/video data, and issues corresponding instructions to theimage/video enhancement processes manager 64 to perform any enhancementsdetermined. In particular, the controller 76 determines whether (and towhat extent) de-noising process 68 and sharpening process 72 are to beapplied to the decompressed image/video data. Additionally, thecontroller 76 (or the image/video enhancement process manager 64) maydetermine whether further enhancements are to be applied to thedecompressed image/video data such as one or more of auto-exposure,auto-white balance, and auto-focus. In one embodiment, de-noising (ifany) is first applied, followed by the (any) application of one or moreof auto-exposure, auto-white balance, and auto-focus, and finallysharpening. More particularly, the following enhancements may beperformed depending on the history information:

-   -   (i) Increase the contrast or brightness of an image to regain or        increase the dynamic range of the original image/video which was        diminished too much; e.g., in compensating for recorder 20        processing performed due to a reduced available network        bandwidth (or parameters related thereto). For example, when one        or more denoising and sharpening processing techniques have been        applied at the recorder 20 and such processing have removed both        high and low frequencies to reduce the amount of network        bandwidth, the resulting in the image/video can be inherently        soft. For example, this can occur when image/video are processed        at the recorder 20 to accommodate network transmissions that        have a bit rate below 1500 Kbps for 640×480 video images.    -   (ii) Remove random, colored dots; e.g., such dots may        particularly occur when at least a portion image/video data is        transmitted wirelessly. Note that in at some embodiments, the        history information may include data identifying whether the        transmission from the recorder 20 includes a wireless        transmission.    -   (iii) Upscaling of the image/video data can be enhanced by        knowing the processing indicated in the history information as        one skilled in the art will understand.    -   (iv) Detecting ringing or blockiness issues in the image/video        data, and then applying a corresponding mitigation enhancement,        as one skilled in the art will understand.

Subsequently, in step 268, upon the image/video enhancement processesmanager 64 receiving instructions from the controller 76, theenhancement processes manager 64 sequentially activates the enhancementprocesses for, e.g., pipelining the decompressed image/video data therethrough as determined by the instructions, and storing the resultingenhanced image/video data in the image/video archive 84. Note thatinformation can be associatively stored with the resulting enhancedimage/video data for determining who or what can access the resultingenhanced image/video data. In various embodiments, one or more of thefollowing data is associatively stored with the resulting enhancedimage/video data for identifying those with access: an identification ofthe recorder 20, an identification of a user, subscriber, or owner ofthe recorder 20 from which the corresponding recorder processedimage/video data was obtained.

Once the resulting enhanced image/video data is stored in theimage/video archive 84, an authorized user may request access to ortransmittal of such enhanced image/video data for viewing as one ofskill in the art will understand.

The present disclosure has been presented for purposes of illustrationand description. Further, the description herein is not intended tolimit the present disclosure to the form disclosed herein. Inparticular, variation and modification commiserate with the aboveteachings, within the skill and knowledge of those having ordinary skillin the relevant art, are within the scope of the present disclosure. Thepresent disclosure is further intended to explain the best modepresently known of practicing the invention as recited in the claims,and to enable others skilled in the art to utilize the presentdisclosure, or other embodiments derived therefrom, e.g., with thevarious modifications required by their particular application or usesof the present disclosure.

APPENDIX

De-Noising.

For simplicity, in the description hereinbelow, the followingdescription and Table A1 provides further specificity.

-   -   Aggressive De-Noising:

De-noising that includes low pass filtering and median filteringcombined with a high degree masking coefficients as one skilled in theart will understand, wherein by “high degree masking coefficients” ismeant Σ_(i−k) ^(i+k)w(t)h(i-t) where k=32-47.

-   -   Moderate De-Noising:

De-noising that includes low pass filtering with masking coefficientshaving a smaller degree (e.g., in the range of 8-31) and in somecircumstance activating a median filter, as one skilled in the art willunderstand.

-   -   Little/No De-Noising:

This term includes no de-noising, de-noising using no low pass filteringor very minor low pass filtering (e.g., “minor” means Σ_(i−k)^(i+k)w(t)h(i-t) where k=0-7), and no median filtering, as one skilledin the art will understand.

Note that in the above description of terms, “Aggressive de-noising”provides more de-noising than “Moderate de-noising” which, in turn,provides more de-noising than “Little/no de-noising”. In one embodiment,as one skilled in the art will understand, the above descriptions forde-noising may be identified more specifically as follows:

TABLE A1 De-noising Description De-noising Technique Aggressivede-noising Gaussian Blur 1.1-1.6, or high pass filter 218-230 Moderatede-noising Gaussian Blur 0.5-1.0, or high pass filter 230-240 Little/node-noising None, or Gaussian Blur 0.01-0.04 (max = 255), or high passfilter 240-255 (max = 255)

De-noising tends to make the resulting image or video appear smoother orhomogenous. Such de-noising may be considered of benefit for animage/photo that does not show many small objects whose details need tobe clear.

Sharpening.

Regarding sharpening, in the description hereinbelow, the followingdescription and Table A2 provides further specificity.

-   -   Aggressive Sharpening:

Activation of a large Gaussian blur technique by the sharpening module44 for processing digital image/video data, wherein by “large Gaussianblur” herein is meant mean 1.6 variance 5, as one skilled in the artwill understand.

-   -   Moderate Sharpening:

Sharpening digital image/video data by performing a minor deconvolution,wherein by “minor deconvolution” herein means mean 0 variance 0.05, asone skilled in the art will understand.

Note that the terms “Aggressive sharpening” provides more sharpeningthan “Moderate sharpening” which, in turn, provides more sharpening than“Little/no sharpening”. In one embodiment, as one skilled in the artwill understand, the above descriptions for sharpening may be identifiedmore specifically as follows:

TABLE A2 Sharpening Description Sharpening Technique Aggressive Amount90-100%, wherein Radius is in a range of 4-6, sharpening and Thresholdis in a range of 4-6. Moderate Amount 60-80%, wherein Radius is in arange of sharpening 1.3-2.5, and Threshold is in a range of 7-9.Little/no No sharpening,, or an Amount 20-40% (max 100%), sharpeningwherein Radius is in a range of 0.2-1.0 (max = 250), and Threshold is ina range of 10-15 (max = 255).Compression.

Regarding compression, in the description hereinbelow, the followingdescription and Table A3 provides further specificity.

-   -   Aggressive Compression:

Activation of a high compression technique by the compressor module 36for processing digital image/video data.

TABLE A3 Compression Description Compression Technique ExtremelyAggressive M-JPEG at >101, or H.264 at greater (High) Compression than401, or JPEG at greater than 101 Aggressive (High) M-JPEG at 51-100, orH.264 at 201-400, Compression or JPEG at 51-100 Moderate CompressionM-JPEG at 11-50, or H.264 at 51-200, or JPEG at 11-50 Little/noCompression None, or M-JPEG at 2-10, or H.264 at 2-50, or JPEG at 2-10,or a loss less compression such as <6.

What is claimed is:
 1. A method for processing data, comprisingperforming the following steps by computational equipment: receiving ata network site of a network, via one or more network transmissions,processed data and a corresponding history information of processingperformed for obtaining the processed data, wherein the processingperformed depends on network data related to a transmissioncharacteristic of the network, the network data obtained for determiningthe processing; accessing the history information for determining:decompression information related to the processed data, and enhancementinformation related to enhancing a visual presentation of the processeddata; decompressing the processed data, thereby obtaining decompresseddata, wherein the decompression information indicates a decompression tobe performed on the processed data; and enhancing one of: the processeddata or the decompressed data according to the enhancement information;and wherein the step of enhancing includes a step of activating one ormore of: a de-noising process, a sharpening process, an auto-exposureprocess, an auto-white balance process, and an auto-focus process forobtaining the enhanced visual presentation.
 2. The method of claim 1,wherein the step of enhancing includes de-noising one of the processeddata or the decompressed data, wherein the de-noising reduces a salt andpepper noise or a Gaussian noise.
 3. The method of claim 2, wherein thenetwork site is operable for performing the steps of claim 1 for each ofa plurality of different instances of the device; wherein for each ofthe instances, resulting data, for a visual presentation derived fromthe processed data and the history information transmitted from theinstance, is obtained, wherein the resulting data is associated withcorresponding authorization data for determining access to thisresulting data.
 4. The method of claim 1, wherein a device forgenerating the processed data is a handheld mobile communicationsdevice.
 5. The method of claim 1, wherein the processed data includesone of: image or video data obtained from first image or video dataobtained at equipment for transmitting to the network site; wherein forobtaining the processed data, the first image or video data iscompressed by one of a first and second data compression process;wherein for the network data being indicative of a first value relatedto the transmission characteristic, the first data compression isperformed, and for the network data being indicative of a moreconstrained second value related to the transmission characteristic, thesecond data compression is performed; wherein the first data compressioncompresses data less than the second data compression.
 6. The method ofclaim 5, wherein enhanced data is obtained from an enhancing of thefirst image or video data, or data derived therefrom; wherein theenhanced data includes data having a first reduction in noise contentobtained from a first noise reduction process when the first datacompression is performed on the enhanced data for obtaining theprocessed data; and wherein the enhanced data includes data having asecond noise reduction process when the second data compressionreduction in noise content from a is performed on the enhanced data forobtaining the processed data.
 7. The method of claim 6, wherein, for thefirst image or video data including video data, the first reductionprocess is identified for reducing more noise in the enhanced data thanthe second reduction process.
 8. The method of claim 5, wherein thehistory information includes the enhancement information, and theenhancement information includes data indicative one or more of thefollowing processes was applied to the first image or video data, dataderived therefrom, for obtaining the processed data: a denoisingprocess, and a sharpening process.
 9. The method of claim 5, wherein thehistory information includes data indicative of whether one or more ofthe following processes was applied to the first image or video data, ordata derived therefrom, for obtaining the processed data: anauto-exposure process, an auto-white balance process, and an auto-focusprocess.
 10. The method of claim 1, wherein the step of activatingincludes at least the denoising and sharpening processes.
 11. Anon-transitory computer-readable medium having machine instructionsstored thereon, the instructions comprising: receiving at a network siteof a network, via one or more network transmissions, processed data anda corresponding history information of processing performed forobtaining the processed data, wherein the processing performed dependson network data related to a transmission characteristic of the network,the network data obtained for determining the processing; accessing thehistory information for determining: decompression information relatedto the processed data, and enhancement information related to enhancinga visual presentation of the processed data; decompressing the processeddata, thereby obtaining decompressed data, wherein the decompressioninformation indicates a decompression to be performed on the processeddata; and enhancing one of: the processed data or the decompressed dataaccording to the enhancement information; and wherein the step ofenhancing includes a step of activating one or more of: a de-noisingprocess, a sharpening process, an auto-exposure process, an auto-whitebalance process, and an auto-focus process for obtaining the enhancedvisual presentation.
 12. The non-transitory computer-readable medium ofclaim 11, wherein a device for generating the processed data is ahandheld mobile wireless communications unit including one of a cameraand a video recorder, wherein the network data is dependent upon one of:a result from a ping by the device of a predetermined network site, adata transmission rate of the network at the device, and a maximumtransmission delay time acceptable by a network site.
 13. Thenon-transitory computer-readable medium of claim 11, wherein the historyinformation includes the enhancement information, and the enhancementinformation includes data indicative one or more of the followingprocesses was applied to the first image or video data, or data derivedtherefrom, for obtaining the processed data: a denoising process, and asharpening process.
 14. A system for processing image or video datacomprising: a network site including the following (a) through (c): (a)a network interface for receiving, via one or more networktransmissions, processed data and a corresponding history information ofprocessing performed for obtaining the processed data, wherein theprocessing performed depends on network data related to a transmissioncharacteristic of a network, the network data obtained for determiningthe processing; (b) a decompressor for decompressing the processed data;(c) a controller for configuring, using the history information, thedecompressor for decompressing the processed data resulting indecompressed data, and for configuring one or more enhancement processesfor enhancing the decompressed data, wherein the enhancement processesinclude at least one noise reduction process for reducing a noise forthe decompressed data, and at least one sharpening process forsharpening a presentation for the decompressed data; wherein the historyinformation identifies processing of image or video data to yield theprocessed data, wherein the history information includes: (i)compression description information related to which of a first andsecond data compressions were performed in obtaining the processed data,and (ii) enhancement description information indicative of image orvideo enhancement processes performed in obtaining the processed data.15. The system of claim 14 further including an enhancement module forenhancing one of: the processed data or the decompressed data accordingto the enhancement information; wherein the enhancement module includesone or more of: a de-noising module for reducing noise in the processeddata or data derived therefrom, and a sharpening process for sharpeningthe processed data or data derived therefrom.
 16. The system of claim15, wherein the enhancement module further performs one or more of: anauto-exposure process, an auto-white balance process, and an auto-focusprocess for obtaining the enhanced visual presentation.
 17. The systemof claim 15, wherein the processed data includes one of: image or videodata obtained from first image or video data obtained at equipment fortransmitting to the network site; wherein for obtaining the processeddata, the first image or video data is compressed by one of a first andsecond data compression process; wherein for the network data beingindicative of a first value related to the transmission characteristic,the first data compression is performed, and for the network data beingindicative of a more constrained second value related to thetransmission characteristic, the second data compression is performed;wherein the first data compression compresses data less than the seconddata compression.
 18. The system of claim 15, wherein enhanced data isobtained from an enhancing of the first image or video data, or dataderived therefrom; wherein the enhanced data includes data having afirst reduction in noise content obtained from a first noise reductionprocess when the first data compression is performed on the enhanceddata for obtaining the processed data; and wherein the enhanced dataincludes data having a second reduction in noise content from a secondnoise reduction process when the second data compression is performed onthe enhanced data for obtaining the processed data.
 19. The system ofclaim 18, wherein, for the first image or video data including videodata, the first reduction process is identified for reducing more noisein the enhanced data than the second reduction process.
 20. The systemof claim 15, wherein the history information includes the enhancementinformation, and the enhancement information includes data indicativeone or more of the following processes was applied to the first image orvideo data, data derived therefrom, for obtaining the processed data: adenoising process, and a sharpening process.